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An integrated DRASTIC model using frequency ratio and two new hybrid methods for groundwater vulnerability assessment

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  • Aminreza Neshat
  • Biswajeet Pradhan

Abstract

Groundwater management can be effectively implemented by mapping groundwater contamination. Intense agricultural activities and land overexploitation have resulted in groundwater contamination, which is becoming a critical issue, specifically in areas where fertilizers are extensively used on large plantations. The goal of this study was to develop an integrated DRASTIC model with a frequency ratio (FR) as a novel approach. Two new hybrid methods namely single-parameter sensitivity analysis (SPSA) and an analytical hierarchy process (AHP) are also implemented for adjusting feature weights to local settings. The FR is used for DRASTIC model rates, whereas both SPSA and AHP are used for DRASTIC weights. The FR-DRASTIC, FR-SPSA and FR-AHP methods are developed; nitrate samples from the same month in different years are used for analysis and correlation (May 2010 and May 2012). The first nitrate samples are interpolated using the Kriging approach. The Kerman plain is used as an example, which is located in southeastern part of Iran. Additionally, the new methods are employed in the study area to compare with each other and the original DRASTIC model. The validation results exhibited that using FR approach improved the correlation between vulnerability index and nitrate concentrations compared with original DRASTIC vulnerability correlation which was 0.37. The results indicated that the new hybrid methods exhibited higher correlation 0.75 in the FR-DRASTIC model. Correlations of the FR-SPSA and FR-AHP approaches were 0.77 and 0.80. Hence, the new hybrid methods are more effective and provide reasonably good results. Furthermore, quantitative measures of vulnerability offer an excellent opportunity to effectively prevent as well as reduce contamination. Copyright Springer Science+Business Media Dordrecht 2015

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  • Aminreza Neshat & Biswajeet Pradhan, 2015. "An integrated DRASTIC model using frequency ratio and two new hybrid methods for groundwater vulnerability assessment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 76(1), pages 543-563, March.
    • Handle: RePEc:spr:nathaz:v:76:y:2015:i:1:p:543-563
    DOI: 10.1007/s11069-014-1503-y
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    1. Gökhan Demir & Mustafa Aytekin & Aykut Akgün & Sabriye İkizler & Orhan Tatar, 2013. "A comparison of landslide susceptibility mapping of the eastern part of the North Anatolian Fault Zone (Turkey) by likelihood-frequency ratio and analytic hierarchy process methods," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(3), pages 1481-1506, February.
    2. M. Chitsazan & Y. Akhtari, 2009. "A GIS-based DRASTIC Model for Assessing Aquifer Vulnerability in Kherran Plain, Khuzestan, Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(6), pages 1137-1155, April.
    3. Majid Roodposhti & Saeed Rahimi & Mansour Beglou, 2014. "PROMETHEE II and fuzzy AHP: an enhanced GIS-based landslide susceptibility mapping," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(1), pages 77-95, August.
    4. Bakhtiar Feizizadeh & Thomas Blaschke, 2013. "GIS-multicriteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia lake basin, Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(3), pages 2105-2128, February.
    5. Hamid Pourghasemi & Biswajeet Pradhan & Candan Gokceoglu, 2012. "Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 63(2), pages 965-996, September.
    6. Saidi, S. & Bouri, S. & Ben Dhia, H. & Anselme, B., 2011. "Assessment of groundwater risk using intrinsic vulnerability and hazard mapping: Application to Souassi aquifer, Tunisian Sahel," Agricultural Water Management, Elsevier, vol. 98(10), pages 1671-1682, August.
    7. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    8. H. Assaf & M. Saadeh, 2009. "Geostatistical Assessment of Groundwater Nitrate Contamination with Reflection on DRASTIC Vulnerability Assessment: The Case of the Upper Litani Basin, Lebanon," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(4), pages 775-796, March.
    9. Baalousha, Husam, 2010. "Assessment of a groundwater quality monitoring network using vulnerability mapping and geostatistics: A case study from Heretaunga Plains, New Zealand," Agricultural Water Management, Elsevier, vol. 97(2), pages 240-246, February.
    10. Stefanos Stefanidis & Dimitrios Stathis, 2013. "Assessment of flood hazard based on natural and anthropogenic factors using analytic hierarchy process (AHP)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 68(2), pages 569-585, September.
    11. Vahid Nourani & Biswajeet Pradhan & Hamid Ghaffari & Seyed Sharifi, 2014. "Landslide susceptibility mapping at Zonouz Plain, Iran using genetic programming and comparison with frequency ratio, logistic regression, and artificial neural network models," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 71(1), pages 523-547, March.
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    3. Shuhang Li & Mohamed Abdelkareem & Nassir Al-Arifi, 2023. "Mapping Groundwater Prospective Areas Using Remote Sensing and GIS-Based Data Driven Frequency Ratio Techniques and Detecting Land Cover Changes in the Yellow River Basin, China," Land, MDPI, vol. 12(4), pages 1-20, March.
    4. Sina Sadeghfam & Yousef Hassanzadeh & Ata Allah Nadiri & Mahdi Zarghami, 2016. "Localization of Groundwater Vulnerability Assessment Using Catastrophe Theory," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4585-4601, October.
    5. Almoayied Assayed & Samer Talozi & Rana Ardah & Nanci Alziq & Siham Bataineh & Aisha Alhushki, 2022. "Using COP Model to Map the Vulnerability of Groundwater Wells Adjacent to Landfills," Sustainability, MDPI, vol. 15(1), pages 1-22, December.

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